XLM RoBERTa XL (xxlarge sized model) XLM RoBERTa XL model pre trained on 2.5TB of filtered CommonCrawl data containing 100 languages. It was introduced in the paper Larger Scale Transformers for Multilingual Masked Language Modeling by Naman Goyal, Jingfei Du, Myle Ott, Giri Anantharaman, Alexis Conneau and first released in this repository. Disclaimer: The team releasing XLM RoBERTa XL did not write a model card for this model so this model card has been written by the Hugging Face team. Model description XLM RoBERTa XL is a extra large multilingual version of RoBERTa. It is pre trained on 2.5TB of filtered CommonCrawl data containing 100 languages. RoBERTa is a transformers model pretrained on a large corpus in a self supervised fashion. This means it was pretrained on the raw texts only, with no humans labeling them in any way (which is why it can use lots of publicly available data) with an automatic process to generate inputs and labels from those texts. More precisely, it was pretrained with the Masked language modeling (MLM) objective. Taking a sentence, the model randomly masks 15% of the words in the input then run the entire masked sentence through the model and has to pr…
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